Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

0

Share

Download to read offline

Research Data Services @ Edinburgh: MANTRA & Edinburgh DataShare

Download to read offline

Presentation at NFAIS seminar on two research data services at the University of Edinburgh: MANTRA and DataShare

  • Be the first to like this

Research Data Services @ Edinburgh: MANTRA & Edinburgh DataShare

  1. 1. NFAIS Open Data Seminar, 16 June 2016 Research Data Services @ Edinburgh: MANTRA & Edinburgh DataShare Stuart Macdonald EDINA & Data Library University of Edinburgh
  2. 2. • Context • University of Edinburgh RDM Policy • Policy implementation • MANTRA • Overview • Online learning module • User profiles • MOOC • Edinburgh DataShare • Background • Scope • Benefits to stakeholders • Metadata • Policies • Future
  3. 3. • EDINA and Data Library are a division within Information Services (IS) of the University of Edinburgh. • EDINA is a Jisc-funded centre for digital expertise providing national online resources for education and research. • Data Library & Consultancy assists Edinburgh University users in the discovery, access, use and management of research datasets. • The Data Library is part of the new Research Data Service – the culmination of a 48 month RDM Roadmap (Phases 0 - 4) to implement the University’s RDM Policy and develop a suite of RDM Services that map onto the research lifecycle to support our researchers. • Data Library Services: http://www.ed.ac.uk/is/data-library • EDINA: http://edina.ac.uk/ Context
  4. 4. University of Edinburgh RDM Policy • University of Edinburgh is one of the first Universities in UK to adopt a policy for managing research data: http://www.ed.ac.uk/is/research- data-policy • The policy was approved by the University Court on 16 May 2011. • It’s acknowledged that this is an aspirational policy and that implementation will take some years.
  5. 5. Policy implementation: RDM Roadmap Research Data Management Roadmap (v.2) http://www.ed.ac.uk/information-services/about/strategy-planning/rdm-roadmap
  6. 6. http://datashare.is.ed.ac.uk/ www.ed.ac.uk/is/data-managementhttp://datablog.is.ed.ac.uk/http://datalib.edina.ac.uk/mantra/ DataStore https://dmponline.dcc.ac.uk/ http://edin.ac/1OF8Auq http://www.ed.ac.uk/is/datasync Ready by mid-2016 http://www.ed.ac.uk/is/research-data-policy Data catalogue in PURE http://www.ed.ac.uk/files/atoms/files/r dm_service_a5_booklet_0.pdf
  7. 7. Research Data MANTRA http://datalib.edina.ac.uk/mantra/
  8. 8. Project funded by Jisc Managing Research Data Programme (2010-2011) Partnership between: • Data Library • Institute for Academic Development Grounded in three disciplinary contexts: social science, clinical psychology and geoscience. Aims to develop online interactive open learning resources for PhD students and early career researchers that will: • Raise awareness of the key issues related to research data management. • Provide guidelines for good research practice. MANTRA overview
  9. 9. Eight units with activities, scenarios and videos: • Research data explained • Data management plans • Organising data • File formats and transformation • Documentation and metadata • Storage and security • Data protection, rights and access • Preservation, sharing and licensing Four data handling practicals: SPSS, NVivo, R, ArcGIS Xerte Online Toolkits – University of Nottingham Online learning module
  10. 10. Online learning module • Delivered online – self-paced, available ‘anytime, anyplace’. • One hour per unit. • Read and work through scenarios & online activities (incl. videos etc). • CC licence to allow manipulation of content for re-use with attribution. • Portable content in open standard formats (e.g. SCORM). • Learning materials deposited with an open licence in JorumOpen and Xpert OER repositories.
  11. 11. Research student: May want to use MANTRA for: • Introduction to concepts and terminology of RDM • Provide an overview of • how to collect, manage data for dissertations, reports, fieldwork • how to plan and develop research projects (data gathering, analysis and storage) • Learn how to use R, SPSS, NVivo or ArcGIS. Career researcher: May want to use MANTRA for: • Reflect on your current data management practice. • Help develop DMPs. User Profiles
  12. 12. Senior academic: May want to use MANTRA for: • Discovering content that might help students and be useful in teaching and learning activities. • Checking content and recommended resources to revise DMPs • Gaining awareness of good RDM practices and benefits of sharing and licensing of their own data. Information professional: May want to use MANTRA for: • Training support staff to increase awareness of institutional data management requirements. • Assisting academics and research students preparing DMPs. • Gaining awareness of the benefits of data sharing and licensing, and digital preservation practices.
  13. 13. • DIY Training Kit for Librarians: an RDM course for librarians covering 5 topics involving reading assignments from MANTRA, reflective writing, and 2-hour F-2-F training sessions, including group exercises. • Fourth release (Sept. 2014) of MANTRA - revised and updated with new content, videos, reading lists, and interactive quizzes. Three of the data handling tutorials were rewritten and tested for newer software versions. • Oct. 2015 - Research Data MANTRA Forum: http://www.jiscmail.ac.uk/mantra-forum
  14. 14. Learners can also proceed at their own pace No formal credit is assigned for the MOOC, Statements of Accomplishment will be available to any learner who completes a course for a small fee. 1 March 2016 - UNC-CH CRADLE team (Curating Research Assets and Data Using Lifecycle Education) and MANTRA launched the Research Data Management and Sharing MOOC. The MOOC uses the Coursera on- demand format to provide short, video-based lessons and assessments across a five-week period.
  15. 15. Edinburgh DataShare http://datashare.is.ed.ac.uk/
  16. 16. • DISC-UK DataShare Project – funded by the Jisc Repositories and Preservation Programme (Mar. 07 – Mar. 09) • A collaborative project exploring new pathways to assist researchers wishing to share data via institutional repositories • Edinburgh DataShare is an open institutional repository of multi- disciplinary datasets produced at the University of Edinburgh. • Tangible deliverable from the project and hosted by the Data Library. • Researchers producing research data associated with a publication, or which has potential use for other researchers, can upload their dataset for sharing and safekeeping. Background
  17. 17. • Available for University of Edinburgh researchers & their collaborators primarily for research projects without a domain repository. • No limits in terms of subject matter or data types. • An IS service since 2010 - RDM Programme funding for development allows enhancements. • DataShare Supports University of Edinburgh RDM Policy (clause 5). • Promoted as part of Research Data Service, one of a range of RDM Services developed for University of Edinburgh researchers • DataShare not for potentially disclosive, commercially sensitive data • Link in PURE Data Catalogue from publication to data record in DataShare Scope
  18. 18. Benefits for stakeholders (funder, researcher, institution) • Edinburgh DataShare acts as a trusted digital repository for research data, where none is designated by a funder. • Data will be discoverable and accessible for others to use beyond the life of a research project. • A permanent identifier can be recorded with your funder to ensure persistent access. • In addition, some publishers require that the data on which a publication is based is made available by the author. • By depositing once you can meet all future requests by researchers wanting a copy of your data.
  19. 19. Metadata and Discoverability • DataShare is a customised DSpace instance. • Selection of DataCite-compliant DCMI metadata fields for discovery of datasets through Google and other search engines via OAI-PMH. • Records are harvested by Data Citation Index. • Citation field automatically generated based on specified metadata values. • Persistent identifier minting (DataCite DOI). • Discovery metadata only; documentation files required to allow re-use (part of manual QA check).
  20. 20. Policies • No mandate for deposit. • Open data or embargo. • Self-deposit model: – Guidance, such as checklist for deposit, user guide with screenshots. – Meetings to discuss data welcome; assisted deposit where warranted. • Basic quality assurance checks by staff (documentation exists, file formats, file integrity). • Creative Commons 4.0 licence by default; open metadata • Preservation policy; depositor agreement; service level definition; recommended file formats, submission policy.
  21. 21. Edinburgh Datashare: Enhancements • Load balancing between 2 remote sites (with automatic failover) • Developmental server established behind University authentication – for depositors to test repository functionality • SWORD (Push) – utilising SWORD API for batch deposit of large and/or many files from remote computers • NEW - Implemented HTML5 resumable upload in the DataShare web interface to allow depositors to easily and quickly deposit individual files up to 15 GB – multiple files can be uploaded by drag ‘n’ drop. • Faceted browsing by data creator, subject classification, keywords, funder for community and collection • Awarded Data Seal of Approval Certification (Oct. 2015) • Research data deposit from RSpace electronic notebook interface into DataShare (prototype)
  22. 22. Future • Streaming multi-media files (files too big to play in browsers) – dependent upon browser choice, plug-ins loaded, network speed • Display multimedia gallery for images • Integrating an SFTP server to allow users to retrieve filesets larger than our current 20 GB limit. • All files downloadable as a zip file. • We anticipate making numerous filesets around 100 GB available in this way in the medium term. • Storage rather than network/browser timeout will become the limiting factor on fileset size. • Move DSpace asset store to a location where more storage space is available
  23. 23. stuart.macdonald@ed.ac.uk Thanks!

Presentation at NFAIS seminar on two research data services at the University of Edinburgh: MANTRA and DataShare

Views

Total views

531

On Slideshare

0

From embeds

0

Number of embeds

1

Actions

Downloads

3

Shares

0

Comments

0

Likes

0

×